Honeywell and Stereolabs Develop Innovative Mobile Solution to Simplify Logistics Across the Supply Chain

Recommendation: Deploy a stereolabs-powered mobile scanning solution today to accelerate inventory scans across the world. Honeywell and stereolabs pair compact, high-quality cameras with a swiftdecoder to deliver fast, reliable data at the point of action. This approach would reduce manual checks, cut cycle times, and provide a clear warning when data is ambiguous or a scan fails.

In practice, the solution integrates into handheld devices and at the conveyor line, turning stored stock into real-time visibility. Field teams can scan items as they move from inbound to outbound, linking the date, batch, and inventory across cameras and sensors. The result: fewer errors, fewer stops, and a smoother flow from dock to delivery.

Innovative features include a fast, swiftdecoder that interprets barcodes and RFID data, robust edge processing, and reliable performance in dim warehouse aisles. This capability supports cameras readings across sites, helping teams move from receiving to outbound inventory in near real-time. Items that are uložené on the dopravník or in racks get updated status and dates automatically, reducing discrepancies.

Partner integration enables Honeywell to align with Stereolabs for a tailored rollout across verticals. Partners can plan replacements or restocking based on real-time counts and date stamps. Engineers commented on the seamless data flow to ERP and WMS systems, while teams see fewer stockouts and more accurate inventory counts across sites.

please implement a phased approach: pilot at a single site, capture feedback, and scale across the network. The integration provides dashboards showing on-hand inventory, inbound, and stored positions with date stamps. By focusing on high-quality data from stereolabs cameras, teams can act swiftly and reduce manual procesy.

Honeywell and Stereolabs Mobile AI for Warehouses: Practical Insights

Begin with a two-week pilot in receiving and put-away zones using ai-enabled, vision-based handheld devices from Stereolabs, integrated with honeywell systems. Set targets: 98% barcode-decoding accuracy, 20–30% faster item locate times, and 95% correct label identification across tasks.

These recommendations help keep operating costs predictable while delivering tangible gains.

What these technologies deliver in practice:

• vision-based recognition identifies items and label data in real time, reducing manual checks and speeding put-away
• barcode-decoding runs on-device to validate SKUs and trigger cross-docking rules across systems
• data-gathering from the camera stream feeds intelligence dashboards that surface trends like inventory drift and task bottlenecks
• ai-enabled edge processing minimizes latency and keeps sensitive data closer to the point of work
• warning systems alert operators when a mismatch between label, item, and location occurs
• many workflows benefit from automated labeling, position verification, and route optimization across zones

Implementation blueprint (step-by-step):

1. Define success measures: identify KPI targets for accuracy, throughput, and location-labeling correctness.
2. Choose a phased rollout: start with receiving, then expand to put-away and cycle counting.
3. Integrate with data-gathering pipelines and Honeywell’s enterprise software; ensure data flows into a single intelligence view.
4. Train staff on new devices and ensure a smooth handover between human tasks and AI-enabled guidance.
5. Monitor metrics daily during the pilot; adjust models and thresholds based on evidence, then scale.

Practical best practices to avoid common pitfalls:

• Ensure consistent lighting and camera positioning to maximize identification performance across items and labels
• Provide ergonomic mounts and clear labeling to minimize occlusion and glare
• Establish standard label formats and verify barcode quality at receiving to reduce downstream errors
• Set up automatic checks for data-gathering integrity and implement a simple alerting rule for deviations
• Create a feedback loop with the partner team to refine models and thresholds regularly

Data, intelligence, and governance considerations:

• Use vision-based streams to build a continuous learning loop; log events to a centralized data store for analytics
• Protect sensitive operational data with edge processing and controlled cloud access; document data lineage for compliance
• Leverage historical data to calibrate AI models and improve identification over time

How to proceed and where to visit:

• Discuss with a partner to tailor the workflow to your facilities; request a demonstration and a pilot plan
• Visit Honeywell and Stereolabs product pages to understand device specs and integration options
• Label strategies and item identification improvements can scale across more sites with consistent results

If you want to dive into the data, request a reference dashboard that highlights item movements, exceptions, and process intelligence.

Honeywell and Stereolabs Develop an Innovative Mobile Solution to Simplify Logistics Across the Supply Chain

Deploy the mobile solution now by equipping all centres with the swiftdecoder scanning stack to enable real-time data-gathering and achieve accurate inventory across the supply chain.

This joint solution blends honeywells software stack with Stereolabs’ depth-aware cameras and the swiftdecoder to deliver real-time scan capabilities that align with existing enterprise systems. It supports services and products, and centralizes data in a single view that makes it easier to determine stock levels, replenishment needs, and shipment readiness at each centre.

To implement, standardize data-gathering across centres, train staff to convert manual checks into automated scans, and connect the software to core systems so data flows instantly. In pilots, teams saw a most noticeable reduction in manual errors and a measurable lift in inventory visibility, with real-time dashboards updated every few seconds and stock reconciliations completed 30% faster.

Across the network, the solution enables collaborating teams to share product knowledge, align on service levels, and extend the stack to new products and centres quickly. The future-ready architecture relies on modular software components and cloud services that can determine trends, schedule preventive actions, and support decision-making for future capacity planning.

From a user perspective, the ability to scan items with a mobile device reduces training time and accelerates task completion, boosting productivity and allowing operators to focus on higher-value activities like picking accuracy and faster restocking.

How the mobile AI tool integrates with existing WMS and ERP workflows

Configure a single, shared API layer that maps WMS events to ERP actions in real time. This approach minimizes manual data entry and keeps honeywell’s ai-enabled mobile tool aligned with most providers’ workflows, delivering a reliable, end-to-end data stream across the supply chain.

Define data contracts that contain fields for product, label, batch, quantity, location, and timestamp, plus order and centre identifiers. Ensure the model supports inbound receipts and outbound shipments so WMS and ERP stay synchronized. Include data feeds from scales to capture weight and from cameras to verify labels, reducing errors and enabling better containment of discrepancies.

SwiftDecoder from stereolabs processes camera frames to identify products and capture attributes in real time. By reading barcodes and visual labels, it accelerates item-level updates and supports accurate lot tracking across centres.

The integration delivers a seamless operating flow: receipt scans trigger ERP inventory updates, putaway actions drive WMS location changes, and picking aligns with order records. The tool feeds signals to ERP for financials and to WMS for order status, while dashboards highlight exceptions and opportunities to improve processes at scale.

Commented by the chief logistics officer, the collaboration between honeywell and stereolabs reduces manual checks and accelerates cycle times. Collaborating across centres, their teams have demonstrated smoother workflows, with label reading accuracy improving and product visibility expanding.

To scale from pilot to full rollout, start with a small set of products in two centres, then extend to more products and locations. The system handles thousands of SKUs, supports multi-centre operations, and can contain product families within a unified data model, ensuring continuity across operating environments.

Key recommendations: align staff training with the new workflow, ensure access to label- and camera-based guidance, and monitor KPIs such as data accuracy, time-to-ERP updates, and reductions in manual entries. Plan for ongoing improvements with providers and internal teams to sustain momentum as you add more products and centres.

Frontline app capabilities: real-time guidance, scanning, and anomaly alerts

Please enable real-time guidance on every pick, scan, and pack action to cut search times and tighten inventory accuracy across warehouses. Configure anomaly alerts to notify those responsible within seconds, so mislabels, quantity mismatches, and stored deviations surface immediately while you visit the dashboard for quick review.

• Real-time guidance: On-screen prompts direct the operator through each step, offer the most direct route, and adjust as inventory moves. This reduces walk time and search time by up to 25%, boosting productivity for those executing tasks across multiple facilities.
• Scanning capabilities: Scan barcodes, QR codes, and labels with the device camera or optional wearables. Stereolabs technology enhances item identification on crowded shelves, even when labels are damaged, and supports offline operation to keep workflows moving. The system identifies the product from stored data and updates the inventory in real time.
• Anomaly alerts: Detect quantity mismatches, mislabels, and missing items, and surface high-priority alerts to those collaborating teams. Each alert includes the product, location, date, and batch details to help identify the root cause quickly and assign the right provider or organization to act.
• Data visibility and integration: Integrates with solutions across ERP, WMS, and services from providers, delivering a single view of inventory, location, and product data. Managers can dive into dashboards to identify trends by date and warehouse, helping visit planning and continuous improvement.
• Operačný dopad: Scales to fit from small distribution centers to large warehouses, enabling organizations like Braun to simplify processes, boost productivity, and keep most products stored accurately. The workflow supports those who are collaborating across networks to identify issues early and keep their supply chains moving smoothly.

1. Implement a 60-day pilot in two to three warehouses to establish baseline metrics and validate a 10–20% improvement in scan-to-pick cycle times.
2. Set anomaly alert thresholds by product family and storage zone, then adjust daily during the first week based on observed false positives and true positives.
3. Publish a simple visit-to-action protocol: when an alert appears, assign a clear owner, include a link to the root-cause view, and require a resolution date to close the loop.
4. Train frontline teams with short, repeatable sessions focused on scanning, guidance prompts, and escalation steps, targeting a minimum 85% in-system task completion within 30 days.
5. Track key metrics such as number of scans per hour, inventory accuracy by product, and anomaly-resolution time to quantify impact for those organizations and providers using the platform.

Pilot to scale: defining timelines, milestones, and success metrics

Recommendation: launch a 12-week pilot with four milestones and a concrete plan to scale, led by a chief sponsor from Honeywell and a partner from Stereolabs. The plan centers on eliminating manual checks by using a software solution and vision-based intelligence to capture items, scans, and processes in a live warehouse environment. This setup creates a tangible path for the future of logistics that is easier to manage and measure.

Timeline and milestones: Week 1–2 cover onboarding, system integration, and establishing secure data tunnels for transmissions from system to cloud. Milestone 1 at Week 3 verifies 75% of items scanned with accuracy above 99%. Milestone 2 at Week 6 reaches 90% of processes digitized. Milestone 3 at Week 9 delivers a 20% increase in throughput. Milestone 4 at Week 12 confirms ROI and readiness to scale to three additional sites.

Success metrics: Determine KPIs that quantify impact and track progress against baseline. Target metrics include scan rate per minute, items processed per hour, order-cycle time reduction, defect rate per thousand scans, labor hours saved, and on-time shipment rate. A real-time dashboard pulls data from the system, enabling quick corrections and a clear finding path for continuous improvement. A nine-month horizon shows solid ROI and scalable capacity across warehouse networks.

Data strategy and governance: Capture data from items, scans, locations, and timestamps, routing it through secure data tunnels to a centralized analytics layer. Ensure data quality, maintain audit trails, and protect sensitive information. Use the findings to refine the plan, adjust workflows, and optimize the intelligence layer for future deployments across logistics services.

Roles and rollout plan: appoint a chief logistics sponsor and assign dedicated Honeywell services and Stereolabs engineering teams as the primary partner. Define decision rights, escalation paths, and cadence for weekly reviews. Document minimum viable features, alignment with existing workflows, and a phased scale route that would expand to new sites on a schedule aligned with inventory cycles and training calendars.

Data privacy, security controls, and governance for AI vision in warehouses

Adopt a zero-trust access model for AI vision pipelines, encrypt all uploaded video frames and sensor data in transit and at rest, and enforce least-privilege permissions for operators and external partners.

Limit capturing to essential items and moments; apply high-quality on-device processing to reduce data movement; use precise label rules to separate training data from live feeds, and ensure data flows are auditable.

Map the источник of each data stream to ensure provenance, and store only data needed for processes in logistics centers. Include items metadata and scan codes when appropriate.

Implement software-based controls with encryption at rest, TLS in transit, and tamper-evident audit logs; align with ISO 27001 and NIST guidelines; monitor for unauthorized access.

Governance requires a cross-functional council with clear roles; the smith and braun leads oversee policy, while stereolabs data engineers provide technical input.

Define data retention windows by data type (frames, metadata, labels) and automate deletion to prevent buildup across many technology stacks; label data according to purpose.

Monitor access attempts and data flows across tunnels, from hubs to logistics centers; track most data movements and generate alerts on anomalies; require scans of commands before action.

Vendor governance: require vendors to provide assurance reports, restrict data sharing with third parties, and require opt-in language for updates to models.

Incident response: maintain playbooks for data breach events, including steps to isolate AI vision services, rotate credentials, and notify stakeholders.

Financial impact: estimating ROI, productivity gains, and cost savings

Implement a 90-day pilot to validate ROI and capture real-time gains across centers and many warehouses, leveraging honeywells data-gathering capabilities to quantify impact.

In this plan, the solution integrates into everyday processes when operating at scale, delivering improvements in barcode-decoding speed, optical verification, and camera-based data capture that feed into real-time dashboards for logistics teams.

To estimate ROI, compare the baseline metrics against post-implementation results: labor hours, throughput per shift, error rates, and asset utilization. Focus on tangible savings from reduced manual entry, fewer mis-shipments, and smoother handoffs between receiving, put-away, picking, and shipping.

Adopt a future-ready approach by expanding into more warehouses and centers using the same tool, ensuring data becomes a single source of truth for the business plan and continuous improvement initiatives.